Can I Run / Qwen3.5-27B / on NVIDIA RTX 3090 Ti
Can I Run Qwen3.5-27B on a NVIDIA RTX 3090 Ti?
Yes
Runs comfortably at Q6_K — minimal quality loss.
Model size
27.8B
GPU memory
24.0GB
Smallest quant
Q3_K_S
Best fit
Q6_K
9 quantizations fit your 24.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q6_KBEST | 23.9 GB | 25.4 GB | 22.4 GB | +0.1 GB |
| Q5_K_M | 20.7 GB | 22.2 GB | 19.6 GB | +3.3 GB |
| Q5_K_S | 20.2 GB | 21.7 GB | 18.9 GB | +3.8 GB |
| Q4_1 | 18.4 GB | 19.9 GB | 17.2 GB | +5.6 GB |
| Q4_K_M | 17.9 GB | 19.4 GB | 16.7 GB | +6.1 GB |
| Q4_K_S | 16.9 GB | 18.4 GB | 15.8 GB | +7.1 GB |
| Q4_0 | 16.6 GB | 18.1 GB | 15.7 GB | +7.4 GB |
| Q3_K_M | 12.6 GB | 14.1 GB | 13.5 GB | +11.4 GB |
| Q3_K_S | 11.7 GB | 13.2 GB | 12.3 GB | +12.3 GB |
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Full model details
Qwen3.5-27B →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
NVIDIA RTX 3090 Ti →
Top-ranked open-source models that fit in 24.0GB.
FAQ
Can the NVIDIA RTX 3090 Ti run Qwen3.5-27B?
Yes. The NVIDIA RTX 3090 Ti's 24.0GB of VRAM is enough to run Qwen3.5-27B at Q6_K quantization (23.9GB required).
What's the best quantization to use?
Q6_K is the highest-precision quantization that fits in your 24.0GB. It uses about 23.9GB of memory and 25.4GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.